Master's Machine Learning Internship 2027 (USA)
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Description
- Internships are 12 weeks paid, with fixed start dates in May or June to accommodate varying school calendars. Depending on the team, our summer internships will be located either remote or hybrid in San Francisco, Palo Alto, New York or Seattle offices
- We offer 2 internship start dates:
- May 17, 2027 - August 6, 2027
- June 14, 2027 - September 3, 2027
- As a Machine Learning Intern at Pinterest, you’ll work on tackling new challenges in machine learning and artificial intelligence
- Throughout your internship, you’ll join our engineering teams as we maneuver through exponential growth and massive scale while building awesome products and features, creating visually rich experiences, spearheading the discovery problem, and pinpointing tomorrow’s engineering challenges
- Lead your own project start to finish to contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
- Gain hands-on experience with production ML systems, including algorithmic research, infrastructure, data engineering, training, inference, and product, to deliver innovative solutions. You will be exposed to full-stack production ML systems
- Leverage frontier AI tools and agents to accelerate engineering implementation, including prototyping and experimentation work
- Validate AI-generated outputs through testing, code review, and critical thinking, ensuring solutions are accurate, maintainable, secure, and aligned with team standards
- Use AI to better understand unfamiliar code, investigate bugs, and summarize technical context or documentation
- Contribute in cutting-edge research in machine learning and artificial intelligence that can be applied to Pinterest problems
- Write clean, efficient, and sustainable code
- Take proactive ownership over the completion and quality of your tasks and project with minimal guidance from your mentor, manager, and peers
- Proficiency with AI-native engineering, including the design of agent-friendly codebases
- Working towards a Master’s degree in Computer Science, ML, NLP, Statistics, Information Sciences or related field
- Mastery of at least one systems language (Java, C++, Python) and one ML framework (Tensorflow, Pytorch, MLFlow)
- Strong communicator and team player. Being able to find solutions for open-ended problems
- High degree of autonomy in learning new agent-first development tools
- Strong critical thinking when working with AI-generated suggestions, with a clear approach to validating correctness, performance, security, and maintainability
- Machine Learning (ranking, computer vision, NLP, content recommendations, embedding, information retrieval etc)
- Comfort iterating on prompts, refining workflows, and adapting AI-assisted approaches based on the problem, context, and constraints
- Experience in research and in solving analytical problems